metadata
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
base_model: salohnana2018/HARD_without_dp_4248_camel_prepocessed_OTE
model-index:
- name: OTE-DAPT-CAMEL-MSA-HARD-4248-SUBSAMPLE-run3
results: []
OTE-DAPT-CAMEL-MSA-HARD-4248-SUBSAMPLE-run3
This model is a fine-tuned version of salohnana2018/HARD_without_dp_4248_camel_prepocessed_OTE on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1685
- Precision: 0.7509
- Recall: 0.7962
- F1: 0.7729
- Accuracy: 0.9548
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 32
- eval_batch_size: 8
- seed: 23
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.1495 | 1.0 | 121 | 0.1123 | 0.7811 | 0.7573 | 0.7690 | 0.9567 |
| 0.0847 | 2.0 | 242 | 0.1201 | 0.7505 | 0.7972 | 0.7731 | 0.9540 |
| 0.0581 | 3.0 | 363 | 0.1314 | 0.7610 | 0.7853 | 0.7729 | 0.9560 |
| 0.0363 | 4.0 | 484 | 0.1529 | 0.7649 | 0.7798 | 0.7723 | 0.9551 |
| 0.0242 | 5.0 | 605 | 0.1685 | 0.7509 | 0.7962 | 0.7729 | 0.9548 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2